Analysis of Normal Plasma Cell Distribution Across Distinct Age Cohorts Reveals Age-Dependent Changes

Abstract

Hematopoietic and stromal cells within the bone marrow (BM) provide membrane-bound and/or soluble factors that are vital for the survival of plasma cells (PCs). Recent reports in murine BM demonstrated the dynamic formation and dispersion of PC clusters. To date, PC clustering in normal human BM has yet to be thoroughly examined. The goal of this study was to determine whether PC clusters are present in human BM and whether clustering changes as a function of age. Quantification of PCs and clustering in BM sections across six different age groups revealed that fewer PCs and PC clusters were observed in the youngest and oldest age groups. PC clustering increased with age until the sixth decade and then began to decrease. A positive correlation between the number of PCs and PC clusters was observed across all age groups. PC clusters were typically heterogeneous for immunoglobulin heavy- and light-chain expression. Taken together, these data demonstrate that PC clusters are present in human BM and that PC clustering increases until middle adulthood and then begins to diminish. These results suggest the spatial distribution of BM PC-supportive stromal cells changes with age:

Keywords

aging bone marrow clustering plasma cells

Introduction

Plasma cells (PCs) are terminally differentiated B lineage cells that produce and secrete large amounts of immunoglobulin (Ig).¹ Following their generation, many PCs enter the bone marrow (BM), which provides unique niches that promote the longevity of PCs.² The BM also plays a key role in the clonal PC malignancy, multiple myeloma (MM), as well as its precursor condition, monoclonal gammopathy of undetermined significance (MGUS). MGUS is an asymptomatic condition that is characterized by a clonal population of abnormal PCs that reside in the BM and has a 1% risk of progression to MM per year.³ The incidence of MGUS has also been shown to increase with age,⁴ which has important implications for MGUS pathogenesis. To begin to understand if aging results in a more permissive BM microenvironment that may predispose to the development of MGUS, in this study, we first wished to determine if the number and spatial distribution of human BMPCs change as a function of age in healthy individuals.

To date, most studies of BMPCs have been performed using mice. Surprisingly, to our knowledge, there have been only two prior studies that quantitated BMPC numbers in humans as a function of age.^5,6 Pritz et al. concluded there are fewer BMPCs in old age using flow cytometry on BM aspirates, and Suzuki concluded that while using immunohistochemistry (IHC), BMPC numbers increased with advancing age until the third decade but then leveled off. Thus, a consensus view on BMPC numbers and age has not yet been reached, although of note, the differing conclusions reached by these two groups may reflect known differences in quantitating BMPCs in BM core biopsies versus BM aspirates.⁷

The BM microenvironment has been shown to be vital to PC survival.⁸ Direct cellular interactions and soluble factors create a specialized microenvironmental niche that distinctively allows PCs to thrive in the BM microenvironment.⁹ Earlier studies suggested that the total number of BMPCs is determined by the number of CXCL12⁺ stromal cells¹⁰ where a single PC contacts a single stromal cell.¹¹ Thus, studies examining the spatial distribution of PCs are needed to determine if human BM niches supporting PC survival are impacted by age. In this regard, Suzuki et al. described that small clusters of 3–5 PCs in BM began to be observed after age 50.⁵ Consistent with this notion, albeit in a murine system, recent intravital and time-lapse imaging has shown that BMPCs can be arranged in clusters and that formation is dynamic with PC clusters forming and then dispersing over time.¹²

Observations of PC clustering during aging in humans suggest the possibilities that with age, PC-supportive stromal cell numbers may change, more than one PC may contact a single stromal cell, or PCs may undergo limited in situ proliferation, thereby generating small clusters of clonally related PCs. Therefore, in this study, we have undertaken a PC-focused analysis of normal human BM across multiple age groups to determine the number of PCs with age, as well as the frequency of PC clusters in BM core biopsies. Our multiplex immunofluorescence (IF) analyses using both heavy-chain (HC) and light-chain (LC) Ig-specific antibodies also permitted an assessment of the clonal relationship of PC clusters in human BM.

Materials and Methods

Bone Marrow Core Biopsy Samples

This study, which included bone marrow core biopsies (BMCBs) from the right and left iliac crest from 60 patients, was performed with the approval of the Mayo Clinic Institutional Review Board. Informed consent was obtained in accordance with the Declaration of Helsinki. BMCBs selected for analysis in this study were determined by Mayo Clinic hematopathologists to have normocellular BM, normal trilineage hematopoiesis, and no morphologic features of metastatic malignant cells. Ten BMCB specimens were obtained for each of the following 6 age ranges: 5 months–9 years, hereafter referred to as 0–9 years; 10–19 years; 20–39 years; 40–59 years; 60–79 years; and 80–99 years. The cohort of 60 patients included 29 males and 31 females.

BMCB Sample Processing

All BMCBs were processed by the Hematopathology Morphology and Histology laboratory at Mayo Clinic, Rochester, MN, as previously described.¹³

IF Staining

Slides were deparaffinized, rehydrated, and processed with antigen-retrieval buffer as previously described.¹³ Following processing, a wax ring was drawn around the BMCB section using a hydrophobic pen so that small volumes of solutions could be added to the slides. To help decrease background staining, three drops of Background Sniper solution (Biocare Medical, Pacheco, CA) were added to the slides for 10 min. Following aspiration of Background Sniper solution, slides were incubated with primary antibodies diluted in a DaVinci Green diluent (Biocare Medical, Pacheco, CA). Slides were first incubated with both goat anti-human lambda LC-TRITC 1:100 and goat anti-human kappa LC-FITC 1:100 and imaged. Antibodies were then stripped from slides as previously described.¹³ Slides were then reblocked and incubated with goat anti-human IgA-TRITC 1:100 and goat anti-human IgG-FITC 1:100 (Southern Biotech, Birmingham, AL). For cytokine staining, sequential slide sections were processed and then individually incubated with mouse anti-human TNFSF13 (Aprily-2, Enzo, Farmingdale, NY); mouse anti-human CXCL12 (Thermo Fischer, Waltham, MA); and rabbit anti-human CD271 (Genetex, Irvine, CA). Staining for total PCs in combination with TNFSF, CXCL12, or CD271 was achieved by then incubating slides with both goat anti-human lambda LC-FITC 1:100 and goat anti-human kappa LC-FITC 1:100 (Southern Biotech, Birmingham, AL). Diluted primary antibody was added to the wax ring area and incubated for 1 hr at RT. Following incubation, slides were subjected to four 5-min washes with Tris-buffered saline (TBS) containing 0.03% Triton-X. If the primary antibody was not conjugated, specimens were then incubated with a 1:500 dilution of either anti-mouse-Ig-Cy3 or anti-rabbit-Ig-Cy3 (BioLegend, San Diego, CA) for 45 min at room temperature (RT). If the slides were incubated with a secondary Ab, they were again washed as described after incubation with primary antibodies. Because BMCB tissue possesses inherently high autofluorescence, as a final step, slides were incubated with 1× TrueBlack Lipofuscin Autofluorescence Quencher (Biotium, Fremont, CA) for 30 s as we have previously described.¹³ Subsequently, slides were subjected to three 1-min washes with phosphate-buffered saline (PBS). Ten microliters of VECTASHIELD Antifade Mounting Media (Vector Labs, Burlingame, CA) containing DAPI was then added to the slides prior to coverslip placement and sealed using nail polish. Slides were stored at 4°C until imaged.

Slide Viewing and Image Capture

An Olympus BX53 fluorescence microscope (Olympus, Center Valley, PA) equipped with an automated stage and Olympus cellSens software was used to initially obtain a full tissue overview scan at 4×. At this low power magnification, specific staining cannot be clearly discerned in whole tissue scans, and thus, bias to areas of high PC content is not considered to be a factor when selecting regions of interest (ROIs). A 20× ROI rectangular indicator was then randomly placed over a piece of tissue such that tissue was observed to fill the rectangle. Five to 10 rectangular 20× ROIs were selected based on tissue availability from the overview scan. The locations of these ROIs were then recorded, and images of each ROI were captured at 20× magnification. A counting grid was applied to each image, and kappa and lambda LC PCs and PC clusters were manually quantified by a single investigator.

Graphing and Statistical Analysis

All data illustrated in bar graphs are represented as the mean ± standard error of the mean (SEM). Data heterogeneity was demonstrated using box and whisker plots where whiskers represent upper and lower extremes, the median is indicated by a line, and the mean is signified by a + sign. Correlation between PC number and the number of PC clusters was determined by calculating a Pearson coefficient. A one-way analysis of variance (ANOVA) test was used to determine overall significant differences in the means of the age groups while a Tukey test was used to determine which group means were significantly different from one another.

Results

PCs in Human BM

To determine whether there are differences in the number of PCs and the number of PC clusters among different age groups, we quantitated the number of Ig LC-expressing PCs (kappa and lambda) for each of 10 patients across six age groups. Depending upon tissue availability, 5–10 distinct ROIs were imaged on each patient slide and analyzed for the total number of PCs, the number of single PCs, and the number of variously sized PC clusters. Fig. 1A (panels I–VI) illustrates representative ROIs from each patient age group, and Fig. 1B demonstrates typical PC clusters (doublets, 3–5 PC clusters, and 6 or more PC clusters) found in human BM. Of interest, analysis of the ROIs from each patient revealed that both the number of PCs and the number of PC clusters varied from ROI to ROI within the same patient. Indeed, Fig. 2A and B illustrates the variability in PC number and number of PC clusters within ROIs from the same patient. Likewise, box and whisker plots of the number of PCs and the number of PC clusters per ROI for each patient within an age group revealed clear differences between patients. Box and whisker plots from the 20–39 years age group (Fig. 2C and D) are shown as representative data illustrating the variability seen within each age group analyzed.

Figure 1.

Detection of PCs in human bone marrow. (A) Kappa PCs (green), lambda (red) PCs, and DAPI (blue) were detected in BM from the following age groups: (I) 0–9 years of age; (II) 10–19 years of age; (III) 20–39 years of age; (IV) 40–59 years of age; (V) 60–79 years of age; (VI) 80–99 years of age. (B) Kappa (green) and lambda (red) PCs found in bone marrow of 60- to 79-year-old patients. Arrows point to representative PC clusters. Scale bar shown in white is 50 mm.

Figure 2.

Intra- and inter-patient heterogeneity among the number of PCs and PC clusters. (A, B) Examples of BM ROIs from the same patient in the 20–39 years age group. Kappa PCs (green), lambda PCs (red), and DAPI (blue). (C, D) Box and whisker plots illustrating the variability in the total number of PCs and PC clusters observed per ROI for each patient in the 20–39 years age group. Median is indicated by line, and mean is signified by + sign. Results from the 20–39 years age group are shown as representative data for the variability seen within each age group. Scale bar shown in white is 50 mm.

Both Younger and Older Patients Tend to Have Fewer PCs and PC Clusters

Analysis of the mean number of PCs per ROI for each age group (Fig. 3A) revealed that both younger (0–9 years of age) and older patients (80–99 years of age) had fewer PCs on average than patients in the mid-age-range groups (10–19, 20–39, 40–59, and 60–79 years of age). The mid-age-range groups were also found to have a greater average number of clusters than the younger and older patients (Fig. 3B). Significant differences between age groups are indicated on the graphs by brackets and asterisks. To determine if there was a correlation between the average number of PCs and the average number of PC clusters, a Pearson correlation coefficient (r value) was calculated for each age group. The r values were all found to be positive and to range from 0.82 to 0.95 (data not shown), thus indicating a positive correlation between the number of PCs and the number of PC clusters. Given that a positive Pearson correlation coefficient was observed between the number of PCs and the number of PC clusters for each age group, we combined the data from all age groups and graphed the number of PCs and the number of PC clusters and calculated a Pearson coefficient, which was found to be 0.91 (Fig. 3C).

Figure 3.

Total PCs and total PC clusters in human BM vary with age. (A) The total number of PCs per ROI and (B) the total number of PC clusters per ROI, over the six age groups. (C) Correlation between the number of PCs and number of PC clusters observed in ROIs. Analysis included patients from all age groups. To account for BM cellularity, we calculated a cellularity multiplier and applied it to the total PC and total PC cluster counts from all patients in age groups of 10 years and older. The graphed results are shown in panels D–F. (D) The total number of PCs per ROI relative to BM cellularity. (E) The total number of PC clusters per ROI, over the six age groups, relative to BM cellularity. (F) Correlation between the number of PCs and number of PC clusters relative to BM cellularity observed in ROIs. Analysis included patients from all age groups. Significant differences (p<0.01) between age groups are indicated with an asterisk (*).

Both Younger and Older Patients Tend to Have Fewer PCs and PC Clusters Even When Accounting for BM Cellularity

Given that BM cellularity is known to decrease with age,¹⁴ we wanted to account for differences in cellularity among our patient groups. Thus, BM cellularity was obtained from the hematopathology report for each patient (Appendix Table IA and B), and we calculated the average BM cellularity for each age group. A cellularity multiplier was calculated by taking the age group with highest cellularity (0–9 years of age group) and dividing it by the cellularity of the other age groups. The resulting factors were then applied as a multiplier to the total PC and total PC cluster counts of the other age groups (Figures 3D and 3E). Adjusting for cellularity using our multiplier method primarily resulted in increasing the number of PCs and PC clusters for the patients in the two oldest age groups (60–79 and 80–99). We again tested for a correlation between relative PCs and PC clusters (Fig. 3F) and calculated a Pearson correlation coefficient (r value), which was found to be 0.92.

The Number and Type of PC Clusters in Human BM Varies With Age

Given that PC clusters in human BM can be comprised of varying numbers of PCs, when analyzing clusters, we not only counted the total number of clusters within an ROI (shown in Fig. 3B) but also counted the number of clusters that comprised 2 cells (doublets comprised of either 2 kappa positive cells, 2 lambda positive cells or 1 kappa and 1 lambda positive cell) or 3–5 cells and ≥6 or more cells of various LC combinations (Fig. 4A–C). Analogous to the total number of PC clusters, both the younger (0–9 years of age) and older patients (80–99 years of age) had fewer doublets and clusters comprised of 3–5 or ≥6 cells, as compared to the mid-age-range groups (10–19, 20–39, 40–59, and 60–79 years of age). Indeed, the youngest age group (0–9 years of age) had significantly lower numbers of doublets than all the other age groups and a significantly lower number of clusters comprised of 3–5 cells than the 20–39 and 40–59 years of age groups. The number of clusters comprised of ≥6 cells only differed significantly between the 0–9 and 20–39 years of age groups. To consider which type of cluster was most prevalent in each age group, we examined the percentage of each type of cluster present in each age group. This analysis revealed that for all age groups, doublets were found to be the most prevalent type of cluster present and accounted for over 60% of all clusters (Fig. 4D).

Figure 4.

The number and type of PC clusters in human BM varies with age. (A) The total number of PC doublets per ROI (includes kappa, lambda, and kappa/lambda doublets). (B) The total number of PC clusters comprised of 3–5 cells. (C) The total number of PC clusters (comprised of 6 or more cells) per ROI. Significant differences (p<0.01) between age groups are indicated with an asterisk (*). (D) Comparison of the percent of various PC clusters found in BM across the different age groups.

Total Number and Percentage of Single PCs

Given that not all PCs in human BM are involved in PC clusters, we also quantified how many PCs were single PCs in each ROI. As shown in Fig. 5A, the 0–9 years of age group had the fewest number of single PCs per ROI as compared to the other age groups while the 10–19 years age group had the largest number of single PCs. In subsequent age groups, the number of single PCs tended to decrease with age. In Fig. 5B, we determined the percentage of single PCs and the percentage of PCs in clusters as compared to the total number of PCs/ROI (Fig. 5B). From this analysis, three notable findings were observed; the 0–9 years of age group had the largest percentage of single PCs; the percentage of single PCs tended to decrease with age; and the 40–59 years age group had the lowest percentage of single PCs.

Figure 5.

Total number and percentage of single PCs. (A) The total number of single PCs and (B) the percentage of single PCs and PC clusters in relation to the total number of PCs. Significant differences (p<0.01) between age groups are indicated with an asterisk (*).

Ig HC and LC Analysis of PC Clusters

To determine if BMPC clusters contained potentially clonal PCs, we first stained BM biopsies with kappa and lambda Ig LC antibodies and identified PC clusters. The location of these clusters on the biopsy was recorded, the antibodies were then stripped from the slide and analyzed to ensure antibody removal was successful, and then sections were re-stained using IgG and IgA HC-specific antibodies. Fig. 6 demonstrates LC and HC analysis of seven different PC clusters and their resulting HC and LC Ig isotypes. Varying combinations of LC and HC were observed for the majority of the seven PC clusters.

Figure 6.

Heavy- and light-chain analysis of PC clusters. (I) Seven PC clusters (labeled A–G) were initially analyzed for expression of Ig LCs, kappa (green)/lambda (red). (II) Subsequent antibody stripping and restaining of the same clusters for Ig HC expression, IgA (orange)/IgG (teal). (III) Resulting heavy- and light-chain Ig isotypes in PC clusters. Scale bar shown in white is 20 mm.

CD271, CXCL12, and TNFSF13 in Human BM Samples

Given that the survival of PCs in the BM is known to depend on interaction with various cytokines including CXCL12 and TNFSF13 (also known as April),¹² as well as various cell types including BM stromal cells, we investigated the presence of CXCL12 and TNFSF13 in a subset of BMCBs from each age group. CD271⁺ cells are known to be a marker of mesenchymal stem cells (MSCs)¹⁵; therefore, we also stained for CD271. CD271⁺ cells were found to be prevalent in the BM, and a representative image is shown in Fig. 7A. PCs, whether single or in clusters, tended to be in close proximity to CD271⁺ cells (Fig. 7B–E). Examination of CD271 expression in a limited number of BMCBs across our patient age groups revealed that CD271⁺ cells were found to be prevalent in the BM of all age groups (Appendix Fig. 1) with a slight increase in expression being observed in patients in the second decade and beyond. By contrast, both TNFSF13 and CXCL12 were found to be scattered throughout the BM of all ages but only occasionally were PCs and PC clusters found to be in close proximity. Representative images are shown in Fig. 7F and G.

Figure 7.

Analysis of CD271, CXCL12, and TNFSF13 in human BM samples. (A) Staining of human BM from a patient in the 20–39 years age group for CD271 (red), PCs (green), and DAPI (blue). Scale bar shown in white is 20 mm. (B–E) Proximity of CD271+ cells and PCs from a patient in the 20–39 years age group. Scale bar shown in white is 10 mm. (F) Staining of human BM from a patient in the 20–39 years age group for CXCL12 (red), PCs (green), and DAPI (blue). (G) Staining of human BM from a patient in the 40–59 years age group for TNFSF13 (red), PCs (green), and DAPI (blue). Scale bar shown in white is 20 mm.

Discussion

During the aging process, the BM is known to undergo several changes that include decreased cellularity, a decline in adaptive immunity, anemia, and increased risk of developing myeloproliferative disorders.¹⁶ Aging also increases the risk of developing the benign PC disorder MGUS, which can progress to the aggressive PC malignancy MM.¹⁷ Given our long-standing interest in normal PCs as well as abnormal PCs in MGUS and MM, in the current study, we sought to determine if the number and spatial distribution of human BMPCs changes as a function of age in healthy individuals. As mentioned earlier, previous studies have examined human BM for PC content using flow cytometry or IHC. However, the current study is the first to determine PC content and Ig isotype expression as a function of age by using multiplex IF to examine human BM core biopsies, thus, allowing visualization of PCs in situ. In this regard, our quantification of the total number of PCs and PC clusters initially revealed that PCs were not always evenly distributed in the BM and that BMPCs were often found in clusters of two or more cells. PC clustering has previously been reported in the BM of adult mice.^12,18 Indeed, Mokhtari et al.¹⁸ reported that spatial organization of cells in murine BM is not uniform and that uneven distribution of BMPCs as well as PC clustering is due to colocalization of BMPCs with stromal cells and eosinophils within BM niches. Although the precise components comprising BM niches are not yet clear, it is believed that cells within the niche provide PCs with essential membrane-bound molecules and secreted proteins. In this regard, both CXCL12⁺ stromal cells and TNFSF13 have been shown to be key survival factors for BMPCs in mice. Benet et al.¹² demonstrated that TNFSF13-deficient mice possess fewer PC clusters and thus concluded that PC clustering may be dependent upon the production and presence of TNFSF13. Although thorough examination of TNFSF13 distribution in human BM has not currently been reported, an inverse relationship between TNFSF13 plasma levels and age has been demonstrated¹⁹ and may account for fewer PC clusters being observed in older adults. Our analysis of both CXCL12 and TNFSF13 in human BM did not reveal a distinct difference in expression among the different age groups nor was a direct relationship between the presence of CXCL12 or TNFSF13 and BMPC clusters observed. However, a larger scale investigation of whether CXCL12 and/or TNFSF13 expression changes as a function of age in humans would be of interest.

Because IF staining for chemokines such as CXCL12 in human BM can be challenging,²⁰ we also stained for CD271. CD271 is a transmembrane neurotrophin receptor and is a marker for MSCs.¹⁵ MSCs in the BM secrete critical cytokines and chemokines, which can mediate the migration of PCs to the BM and maintain retention of PCs within the BM. In our studies, analysis of normal BM for the presence of CD271 revealed a robust expression in all age groups. In addition, both single PCs and PC clusters were typically located adjacent to a CD271⁺ cell. Thus, it is possible that BM CD271⁺ cells express PC survival factors that may aid in PC migration and retention. In this regard, a significant number of publications have demonstrated MSC cytokine and chemokine expression (reviewed in the works of Song et al.²¹ and Kuci et al.²²).

The number of PCs within the BM has previously been shown to vary as a function of age in both mice¹⁷ and in limited studies in humans.^5,6 Our study is the first quantification of BMPCs across multiple age groups and is the first to include two younger age groups (5 mo to 9 years and 10–19 years). Similar to murine studies, we found that the oldest patient group in our study had fewer BMPCs and BMPC clusters on average than the mid-age-range groups.²³ The decrease in BMPCs in older adults is believed to be the result of both decreased PC generation due to lower germinal center activity in older adults and the cellular alterations that occur in the aging BM microenvironment, which may affect PC homing and retention.⁶ Notably, fewer PCs and PC clusters were also found in our youngest age group. Early on in life, the adaptive immune system is not yet fully mature, and fewer PCs may be generated due to the presence of fewer marginal zone B cells, lower B-cell activation capacity, and fewer antigen encounters.²⁴ Pihlgren et al.²⁵ reported that in infant mice, PCs have difficulty establishing themselves in the BM due to the lack of survival signals while Belnoue et al.²⁶ more specifically attributed the defect to lack of sufficient TNFSF13 production early on in murine life.

The PC malignancy MM and its precursor condition MGUS both involve the expansion of clonal PCs.²⁷ Given that the risk of MGUS increases with age, in this study, we wanted to determine if BMPC clusters involved clonal PCs, especially in our older age groups. Although our examination was limited, PC clusters were typically found to be comprised of both kappa and lambda LC-expressing cells with various combinations of HC isotypes. Thus, PC clustering did not tend to involve local in situ clonal PCs in any of the age groups tested and suggests that clustering results instead from the ability of several PCs to make contact with supportive stromal cells that may secrete factors that promote PC survival and retention in the BM.

The current findings suggest that PCs can arrange in clusters within the BM at any age and that PC clustering is positively correlated with the number of BMPCs. PC clustering was also found to increase with age but then diminished in older adults. Further studies to understand the mechanisms responsible for PC clustering in normal BM are warranted.

Footnotes

Appendices

Appendix Table IIB.

Complete Blood Cell Results for Patient Cohort.

	Peripheral Blood						WBC Differential
Age Group	Hgb ×g/dL	RBC ×10¹²/L	MCV fL	RDW%	WBC ×10⁹/L	PLT ×10⁹/L	Np%	Lym%	Mc%	Eos%
40–59 years
1	11.5	3.7	96.4	13.1	7.0	116.0	53.0	19.0	26.0	1.0
2	13.5	4.5	87.6	12.3	7.1	247.0	76.0	17.0	3.0	3.0
3	15.9	4.9	93.7	13.1	11.2	327.0	73.0	20.0	4.0	2.0
4	11.8	3.9	88.9	12.7	9.9	332.0	86.0	10.0	1.0	3.0
5	13.3	4.8	87.4	14.0	9.7	318.0	75.0	16.0	7.0	2.0
6	11.2	4.0	84.0	12.6	9.6	372.0	59.0	28.0	8.0	4.0
7	13.9	4.2	95.3	12.6	8.5	331.0	72.0	19.0	6.0	3.0
8	13.5	4.6	84.9	12.9	6.2	206.0	53.0	40.0	6.0	NA
9	NA	NA	NA	NA	NA	NA	80.0	13.0	7.0	NA
10	13.4	4.5	93.9	14.6	18.8	480.0	76.0	18.0	6.0	NA
Average	13.1	4.3	90.2	13.1	9.8	303.2	70.3	20.0	7.4	2.6
60–79 years
1	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
2	14.6	5.1	84.8	15.1	8.7	196.0	73.0	18.0	8.0	1.0
3	12.6	3.9	93.9	15.5	5.0	241.7	70.0	17.0	7.0	1.0
4	14.6	4.5	96.7	13.8	6.3	229.0	68.0	23.0	5.0	2.0
5	10.7	3.4	93.5	12.6	8.9	209.0	69.0	19.0	9.0	3.0
6	8.4	3.2	87.3	18.9	3.1	90.0	79.0	9.0	11.0	NA
7	11.3	3.9	83.5	16.6	6.7	228.0	75.0	6.0	13.0	3.0
8	10.8	3.7	88.4	15.4	9.2	423.0	75.0	17.0	1.0	5.0
9	NA	NA	NA	NA	NA	NA	49.0	34.0	11.0	5.0
10	NA	NA	NA	NA	NA	NA	65.0	23.0	9.0	3.0
Average	11.9	3.9	89.7	15.4	6.8	231.0	69.2	18.4	8.2	2.9
80–99 years
1	13.1	4.6	85.9	15.5	4.2	61.0	53.0	22.0	23.0	1.0
2	9.6	3.2	96.0	16.8	1.7	95.0	71.0	19.0	10.0	NA
3	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
4	12.1	4.1	92.0	14.0	11.0	247.0	65.0	10.0	18.0	7.0
5	10.3	3.5	86.6	19.2	11.4	483.0	81.0	7.0	5.0	1.0
6	14.0	5.1	84.0	15.5	7.6	264.0	58.0	33.0	4.0	3.0
7	11.8	3.8	95.8	18.0	10.7	186.0	70.0	19.0	5.0	5.0
8	11.7	4.4	84.3	15.7	5.7	183.0	78.0	6.0	15.0	1.0
9	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
10	12.0	4.0	90.3	13.4	5.9	220.0	76.0	8.0	14.0	1.0
Average	11.8	4.1	89.4	16.0	7.3	217.4	69.0	15.5	11.8	2.7

Competing Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Author Contributions

All authors have contributed to this article as follows: research design (DKW, DFJ), data analysis (DKW), writing manuscript (DKW, DFJ), manuscript approval (DFJ).

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the National Institutes of Health (grant CA196831 awarded to DFJ).

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